Update app.py

app.py

@@ -10,7 +10,7 @@ with col1:
     st.markdown("Message spam detection tool for Turkish language. Due the small size of the dataset, I decided to go with transformers         technology Google BERT. Using the Turkish pre-trained model BERTurk, I imporved the accuracy of the tool by 18 percent compared to the previous model which used fastText.")
 with col2:
         text = st.text_input("Enter the text you'd like to analyze for spam.", disabled=flag)
-        st.button('Analyze')
+        aButton = st.button('Analyze')
 if st.button('Load Model', disabled=False):   
     with st.spinner('Wait for it...'):
         import torch
@@ -57,10 +57,11 @@ if st.button('Load Model', disabled=False):
                 prediction = 'Spam' if np.argmax(output.logits.cpu().numpy()).flatten().item() == 1 else 'Normal'
                 pred = 'Predicted Class: '+ prediction
                 return pred
-        flag = False      
+        flag = False
+        text(disabled=flag)      
 if not flag:       
     with col2:
-        if text or st.button('Analyze'):
+        if text or aButton:
             st.header(predict(text))